摘要
用人工神经网络分析人体特征和计算机X射线摄影(CR)参数的定量关系,建立基于身体指数的CR摄影满意度下的人体特征参数、管电压与管电流.曝光时间和CR摄影得分为目标的0-1整数规划模型,用分组过滤方法简化解空间,最后用遗传算法求解.以拍摄胸片(PA)为对象的研究结果表明,CR摄影条件优化方法得到的结论与专家多年临床经验一致,人工神经网络和遗传算法可以在CR摄影中发挥作用,解决实际问题.该研究方法可以应用到CR系统对身体其他部位的摄影并推广到其他X射线摄影设备的应用之中.
The quantitative relation between physical features and computerized radiography （CR） parameters is analyzed with artificial neural network to develop a 0-1 integer planning model based on physical feature parameters, tube voltage, tube current＇ exposure time and CR scoring according to the satisfiability of relevant photos for body indices. Grouped filtering method was used to simplify the solution space, then the optimized model is solved by genetic algorithm. The result of pleurography （PA） indicates that the conclusion drawn by this CR optimization method, is compatible with experts＇ long-time clinical experience and that both the artificial neural network and genetic algorithm play the role in CR and solving actual problems. In addition, this method can be used to analyze the CR photos of the rest of body, and extended to other X-ray photographic equipment.
出处
《东北大学学报（自然科学版）》
EI
CAS
CSCD
北大核心
2007年第5期631-634,647,共5页
Journal of Northeastern University(Natural Science)
基金
国家自然科学基金资助项目(60574050)
关键词
X射线摄影
影像质量
照射剂量
身体指数
人工神经网络
遗传算法
X-ray photograph
image quality
exposure dose
body index
artificial neural network
genetic algorithm
